1a: The aim of the proposed research is to understand pleiotropy: that is the nature, extent, and effect of genetic variation on multiple phenotypes. The extent of pleiotropy in humans is an important open question. Apart from inherent interest, it is directly relevant to the use of human genetics for improving drug development pipelines (see below). By their nature, studies of pleiotropy require data on multiple phenotypes. We aim to investigate pleiotropy using genetic data together with baseline measurements and the biomarker data (as it becomes available).

1b: Our analysis ultimately aims to inform decisions about which genes and pathways are the best targets for drug development. The efficacy and safety of therapeutics depends on the consequences of perturbations, by the drug, of particular gene products. Genetic variants also perturb the nature or amount of gene products, and is informative for drug efficacy, with effects on other phenotypes informative for on-target safety effects. The proposed work, mainly on non-clinical phenotypes, will involve proof-of-principle studies and development of statistical methods. We will make a further application when more clinical phenotypes are available in UK Biobank

1c: The research will use computers to build statistical models of the correlation between the genetic variation in an individual’s genome and biological measurements collected by UK Biobank. We can use the research to ask: if the genetic difference in a gene mimics or is related to the effects of a treatment what is likely to be the (positive and negative) effects of giving it to patients? To do this effectively we will look at the relationship between genetic variation and multiple phenotypes at the same time.

1d: Full cohort.

Project extension:

“We would like to broaden the scope of our investigation using UK Biobank data to enable us to conduct research with increased relevance to healthcare. Specifically, we would like to extend our analyses of associations and correlations between genetic and phenotypic data to the additional clinical traits, such as the hospital episodes statistics / hospital inpatient data (HES) and primary care record (GP) data that is, or soon will be, available via UK Biobank. As per our initial application, we would also require access to all current and future biochemistry/biomarker data as and when this becomes available. We would not require access to any imaging data.

Linking the HES and GP data to genotype data in a large population will facilitate the detection of pleiotropy between a specific variant and a wide range of physiological and clinical outcomes. With reference to your recent guidance, we consider that the proposed broader scope of our project remains ‘hypothesis-generating’ in nature. We would continue to use all the requested data to develop our own statistical models for the analysis of linked genotypic and phenotypic information. Our overall aim remains to use a better understanding of human biology to help inform decisions about which genes and pathways are the best targets for drug development. The additional HES, PCR and biochemistry data will allow for an even better understanding of the efficacy and safety of therapeutics due to the increased clinical relevance of these traits. We may also use the HES and PCR data to define subtypes of a clinical condition based on other data available to us; define severity scales of a clinical condition, again based on other data; or to conduct further pharmacogenetic analyses.”